Heat Extremes in China

WASHINGTON – Humans are responsible for increasingly warm daily minimum and maximum temperatures in China, new research suggests. The study is the first to directly link greenhouse gas emissions with warmer temperature extremes in a single country, rather than on a global scale, according to the paper's authors.

"There is a warming in extreme temperatures over China, and this warming cannot be explained by natural variation," said Qiuzi Han Wen, an author on this paper and a researcher at the Institute of Atmospheric Physics in Beijing, China. "It can only be explained by the anthropogenic external forcings. These findings indicate very clearly that climate change is not just an abstract number for the globe; it is evident at regional scale."

Watts' UHI Fixation

But the only forcing they considered was GHG’s. Nary a word exists in the paper about UHI, urban heat island, station siting, of heat sync (sic) effects.

It's true that the paper doesn't mention UHI. It's likely that is already taken into account as part of the quality control to which the paper refers:

China’s National Climate Center has recently compiled and quality controlled an extensive daily temperature data set [Wu and Gao, 2012]. Records of daily maximum, daily minimum, and daily mean temperatures were collected from 2416 observation stations from 1961 to 2007.

Thing is, if Anthony was correct and the quality control process for some reason omitted to allow for UHI, would one expect the greatest increase in extreme temperatures to be in areas of greatest population growth?

Compare the Maps

Now the maps I've come across don't show population growth but they do show population density. Let's just look at the maps and compare them to the charts showing trends in the maxima (Tx) and minima (Tn) temperatures in the paper (click images to enlarge).

TXx = annual maxima of daily maximum (TXx) temperatures

TNx = annual maxima of daily minimum (TNx) temperatures

TXn = annual minima of daily maximum (TXn) temperatures

TNn = annual minima of daily minimum (TNn) temperatures

Here is a population map from Wikipedia showing that the temperature trends don't align well with areas of greatest population density.

Should we let Anthony know that the population maps of China must be wrong?

5 comments:

It's just extraordinary that Watts tries to keep his UHI charade up...absolute denial in action.

Those maps clearly show the aerosol induced suppression of trends in Txx in the areas most susceptible to pooling polluted air,while the trends in toto are strong or strongest in the least populated areas.

I had a good laugh at one of his in-line replies. When asked about the whereabouts of his much-trumpeted 'new' paper,he said he would not be rushed..Funny, he's more than happy to knee-jerk out this kind of pitiful reaction. Probably should wait for R. Pielke to explain it to him.

It's just stunning that after all the years that Watts has spent "scrutinizing" temperature data, he still hasn't figured out how to perform the very basic analysis necessary to test his claims. Actually, "pathetic" would be a better term than "stunning" -- performing basic data analysis to test Watts' claims requires only high-school math and college-undergraduate computer programming skills).

Anyone who has the above technical skills and makes a serious attempt to analyze the global temperature data (as in actually crunching it to produce their own global-temperature estimates) will quickly discover the following:

1) Even a simplistic gridding/averaging procedure (much simpler than the algorithm that NASA employs) will produce results amazingly similar to the global-average temperature results that NASA publishes.

2) Data from rural vs. urban stations will produce virtually identical global temperature trends. "UHI" just doesn't matter much at all when it comes to calculating temperature *trends*.

3) Raw and adjusted data will produce very similar global-average temperature trends. For global-scale averages, the adjustments for individual stations cancel each other out to an amazing degree.

4) The NASA global-average results can be replicated amazingly closely with data from just a *few dozen* stations scattered around the world. It doesn't matter much if the few dozen stations you select are rural or urban, or if the data you use is raw or adjusted. You will get similar results -- results that line up nicely with the official NASA results -- every time.

To that end, I've put together some software that allows average folks to demonstrate all of the above with just a series of mouse-clicks.

The software combines a simple global-temperature averaging routine with a clickable Google Map front-end; it enables the user to "roll his/her own" global-average temperature results from raw and adjusted data by selecting their his/her own "custom" sets of temperature stations via mouse-clicks. It also displays the official NASA results along with the results from the stations selected by the user to allow a direct comparison with the NASA results.

The software comes in two packages -- the first package is a small download, but is very challenging to set up (as in requiring serious "Unix nerd" command-line skills). The second package is a *much bigger* download, but has everything bundled up in a "virtual machine" file that can be set up and run with just a few mouse-clicks.

The first package (small download but difficult to set up) is available at: https://docs.google.com/file/d/0B0pXYsr8qYS6VUs2c2Z6SVdHZ1k/edit?usp=sharing

The second package (much bigger download, but very easy to set up and use) is available at: https://docs.google.com/file/d/0B0pXYsr8qYS6VUJ4WnpZbS15LWM/edit?usp=sharing

I strongly recommend that folks go for the second package (even if it means waiting a long time to download it all).

Full documentation for the second package can be found at the link on the right side of the download page.

Basically, all you need to run the second package is to install Oracle's free VirtualBox software (available at www.virtualbox.org -- super easy to install via mouse-clicks), import the .ova file into VirtualBox, hit the VirtualBox "start" button and wait a minute or two.

After you do that, you will be able to shoot-down all of Watts' favorite claims about the global temperature record with just a series of mouse-clicks. No kidding!

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All you need to know about WUWT

WUWT insider Willis Eschenbach tells you all you need to know about Anthony Watts and his blog, WattsUpWithThat (WUWT). As part of his scathing commentary, Wondering Willis accuses Anthony Watts of being clueless about the blog articles he posts. To paraphrase:

Even if Anthony had a year to analyze and dissect each piece...(he couldn't tell if it would)... stand the harsh light of public exposure.

Definition of Denier (Oxford): A person who denies something, especially someone who refuses to admit the truth of a concept or proposition that is supported by the majority of scientific or historical evidence.
‘a prominent denier of global warming’
‘a climate change denier’

Alternative definition: A former French coin, equal to one twelfth of a Sou, which was withdrawn in the 19th century. Oxford. (The denier has since resurfaced with reduced value.)